Virtual reality (VR) is one of the hot spots in the computer network world in recent years, which has attracted more and more people’s attention. This study mainly explores the effect of mitigating the psychological trauma of adult burn patients based on the VR technology of smart medical treatment. First, the EEG data are sent to the data processing module through a wireless protocol; then, the data processing module denoises the EEG data and performs feature extraction and feedback parameter calculation; after that, these parameters will be sent to the VR interaction engine; based on this, these parameters change the VR scene to capture and reflect the physiological activities of the patient’s brain in real time; finally, the patient uses the VR scene content presented by the real-time feedback of the captured EEG signal as a guide to making self-adjustment in time, and the electrical signal of captured brain at this time is again transmitted to the next work cycle and continues to feed back and present new VR interactive scenes to guide and intervene in the patient’s self-regulation behavior. The VR feedback training module is responsible for receiving the characteristic data calculated from the EEG acquisition and processing module and converts it into parameter variables that control the VR intervention system. The system user adjusts the state according to the feedback information displayed in the VR scene and generates new EEG signals to promote the realization of self-adjustment. The biofeedback training based on EEG feeds back the intuitive EEG state to the patient, prompting them to learn how to realize self-regulation and achieve the purpose of adjusting the level of mental health. The degree of itching and pain in the VR treatment group was alleviated, and compared with the normal training treatment results, it was statistically significant (
P
>
0.05
). This study has a positive effect on the psychological intervention of patients with facial injuries.
From 2D to VR Film: A Research on the Load of Different Cutting Rates Based on EEG Data Processing